% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bapvar.R
\name{bapvar}
\alias{bapvar}
\title{Run the BaP-VAR model on citation data}
\usage{
bapvar(
  data,
  lags = 1,
  nchains = 2,
  seed = 8086,
  adapt_iters = 1e+06,
  sample_iters = 250000
)
}
\arguments{
\item{data}{A dataframe that should be a subset of the replication data,
giving only the data for one precedent (sorted by citing year)}

\item{lags}{An integer vector of length one giving the number of lags to use
(the default is 1)}

\item{nchains}{An integer vector of length one giving the number of MCMC
chains to generate (the default is 2)}

\item{seed}{An integer vector of length one giving the seed to use for
reproducibility of results (the default is 8086)}

\item{adapt_iters}{An integer vector of length one giving the number of
iterations to use in the adaptation phase (the default is 1000000,
and a large number such as one million is encouraged)}

\item{sample_iters}{An integer vector of length one giving the number of
iterations to use for sampling (the default is 250000,
and a large number such as that is encouraged)}
}
\value{
A list of length two, with elements: "samples", containing an
\code{\link[coda]{mcmc.list}} with the posterior samples;
and "dic", containing a \code{\link[rjags:dic.samples]{dic}} object
with the DIC samples
}
\description{
Run the BaP-VAR model on citation data
}
